






"""simple docstring"""





def 	lowerCamelCase__			(				_lowerCamelCase			:						Optional[int]						,							_lowerCamelCase			:						Union[str, Any]						,							_lowerCamelCase			:						str					) ->							Optional[Any]:
  if n == 0:
    return 1

  elif n % 2 == 1:
    return (binary_exponentiation(_lowerCamelCase						,							n - 1						,							_lowerCamelCase					) * a) % mod

  else:
    lowerCamelCase_       	=		binary_exponentiation(_lowerCamelCase						,							n / 2						,							_lowerCamelCase					)
    return (b * b) % mod


# a prime number
_SCREAMING_SNAKE_CASE   :							str          =		701

_SCREAMING_SNAKE_CASE   :							List[Any]          =		10_0000_0000
_SCREAMING_SNAKE_CASE   :							List[str]          =		10

# using binary exponentiation function, O(log(p)):
print((a / b) % p == (a * binary_exponentiation(b, p - 2, p)) % p)






print((a / b) % p == (a * b ** (p - 2)) % p)












"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


_SCREAMING_SNAKE_CASE   :							List[Any]          =		{'''configuration_plbart''': ['''PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PLBartConfig''']}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _SCREAMING_SNAKE_CASE   :							Union[str, Any]          =		['''PLBartTokenizer''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _SCREAMING_SNAKE_CASE   :							List[str]          =		[
      '''PLBART_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''PLBartForCausalLM''',
      '''PLBartForConditionalGeneration''',
      '''PLBartForSequenceClassification''',
      '''PLBartModel''',
      '''PLBartPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_plbart import PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP, PLBartConfig

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_plbart import PLBartTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_plbart import (
        PLBART_PRETRAINED_MODEL_ARCHIVE_LIST,
        PLBartForCausalLM,
        PLBartForConditionalGeneration,
        PLBartForSequenceClassification,
        PLBartModel,
        PLBartPreTrainedModel,
    )


else:
  import sys

  _SCREAMING_SNAKE_CASE   :							Optional[Any]          =		_LazyModule(__name__, globals()['''__file__'''], _import_structure)




